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roberta-finetuned-WebClassification-v2-smalllinguaMultiv2

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roberta-finetuned-WebClassification-v2-smalllinguaMultiv2 / README.md
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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: roberta-finetuned-WebClassification-v2-smalllinguaMultiv2
    results: []

roberta-finetuned-WebClassification-v2-smalllinguaMultiv2

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8644
  • Accuracy: 0.8387
  • F1: 0.8387
  • Precision: 0.8387
  • Recall: 0.8387

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall
No log 1.0 95 2.3654 0.4409 0.4409 0.4409 0.4409
No log 2.0 190 1.8455 0.5269 0.5269 0.5269 0.5269
No log 3.0 285 1.4468 0.6344 0.6344 0.6344 0.6344
No log 4.0 380 1.1099 0.7419 0.7419 0.7419 0.7419
No log 5.0 475 1.0515 0.7634 0.7634 0.7634 0.7634
1.6355 6.0 570 0.9938 0.7312 0.7312 0.7312 0.7312
1.6355 7.0 665 0.8275 0.7957 0.7957 0.7957 0.7957
1.6355 8.0 760 0.8344 0.7957 0.7957 0.7957 0.7957
1.6355 9.0 855 0.8516 0.8065 0.8065 0.8065 0.8065
1.6355 10.0 950 0.8723 0.7957 0.7957 0.7957 0.7957
0.2827 11.0 1045 0.8644 0.8387 0.8387 0.8387 0.8387
0.2827 12.0 1140 0.9343 0.8065 0.8065 0.8065 0.8065
0.2827 13.0 1235 1.0181 0.7957 0.7957 0.7957 0.7957
0.2827 14.0 1330 1.0068 0.7957 0.7957 0.7957 0.7957
0.2827 15.0 1425 1.0085 0.8065 0.8065 0.8065 0.8065
0.0485 16.0 1520 1.0257 0.8280 0.8280 0.8280 0.8280
0.0485 17.0 1615 1.0305 0.8172 0.8172 0.8172 0.8172
0.0485 18.0 1710 1.0648 0.7957 0.7957 0.7957 0.7957
0.0485 19.0 1805 1.0677 0.7957 0.7957 0.7957 0.7957
0.0485 20.0 1900 1.0687 0.7957 0.7957 0.7957 0.7957

Framework versions

  • Transformers 4.31.0.dev0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3